In this article, we are going to see how to access and modify the value of a tensor in PyTorch using Python.
We can access the value of a tensor by using indexing and slicing. Indexing is used to access a single value in the tensor. slicing is used to access the sequence of values in a tensor. we can modify a tensor by using the assignment operator. Assigning a new value in the tensor will modify the tensor with the new value.
Import the torch libraries and then create a PyTorch tensor. Access values of the tensor. Modify a value with a new value by using the assignment operator.
Example 1: Access and modify value using indexing. in the below example, we are accessing and modifying the value of a tensor.
Python
# Import torch librariesimport torch# create PyTorch tensortens = torch.Tensor([1, 2, 3, 4, 5])# print tensorprint("Original tensor:", tens)# access a value by their indextemp = tens[2]print("value of tens[2]:", temp)# modify a value.tens[2] = 10# print tensor after modify the valueprint("After modify the value:", tens) |
Output:
Example 2: Access and modify the sequence of values in tensor using slicing.
Python
# Import torch librariesimport torch# create PyTorch Tensortens = torch.Tensor([[1, 2, 3], [4, 5, 6]])# Print the tensorprint("Original tensor: ", tens)# Access all values of only second row# using slicinga = tens[1]print("values of only second row: ", a)# Access all values of only third columnb = tens[:, 2]print("values of only third column: ", b)# Access values of second row and first# two columnc = tens[1, 0:2]print("values of second row and first two column: ", c)# Modifying all the values of second rowtens[1] = torch.Tensor([40, 50, 60])print("After modifying second row: ", tens)# Modify values of first rows and last# two columntens[0, 1:3] = torch.Tensor([20, 30])print("After modifying first rows and last two column ", tens) |
Output:
